Recovering three-dimensional (3D) geometry from a single image has been a standing problem in computer vision and computer graphics for a long time. Current techniques only deal with recovering the geometry of solid or deformable objects from two-dimensional (2D) images in the form of polygon meshes. None of the existing work deals with the recovery of the 3D geometry of fuzzy objects, e.g., fire grass, trees, water, etc., particularly to recover the particle systems that could have generated the 2D fuzzy objects in the images.
Recovering 3D information from 2D images is important for future film production systems. One of the important applications is to reconstruct 3D geometry of a scene from a single 2D image, a process known as 2D-to-3D conversion. Because recovering 3D from 2D is an ill-posed problem, human interactions is needed for accurate 3D constructions. Such semi-automatic approaches have been utilized in the 2D-to-3D conversion system developed by a company called In-Three, Inc. of Westlake Village, Calif., which specializes in making stereoscopic films from regular 2D films. The 2D-to-3D conversion system is described in U.S. Pat. No. 6,208,348 issued on Mar. 27, 2001 to Kaye. In the 2D-to-3D process, a geometry dimensionalist has to create 3D geometries or stereoscopic pairs that match objects in the input image. It may be easy for human editors to create or modify the geometries of solid or deformable objects such as buildings and human bodies, but it is very time consuming and difficult for human editors to create 3D geometries to match the fuzzy objects, such as trees and clouds, in 2D images.
Although there has been much prior work on single-view 3D geometry recovery, there appears to have been little focus on recovering the 3D geometry of the fuzzy objects from 2D images. A system and method for recovering the 3D geometry of the fuzzy objects from 2D images is, therefore, desired.